Assessment of electronic sensor data to remotely identify a motor vehicle and monitor driver behavior

ABSTRACT

A computing device is connected to a motor vehicle&#39;s diagnostic port or communication port to acquire vehicle sensor data, for example from various pressure, temperature, oxygen, fuel and other sensors typically installed on a motor vehicle for other reasons. Acquired sensor data is wirelessly transmitted to a remote server where the acquired sensor data can be compared to a database of stored sensor data to identify the motor vehicle. Additional functionality is described that leverages uploaded sensor data. Sensor data may be uploaded to the server in near-real time, and/or buffered locally and uploaded by periodic or episodic, push or pull communication protocols.

RELATED APPLICATIONS

This application is a non-provisional of U.S. Provisional ApplicationNo. 61/657,192 filed Jun. 8, 2012 and incorporated herein by thisreference.

COPYRIGHT NOTICE

© 2012-2013 Airbiquity Inc. A portion of the disclosure of this patentdocument contains material which is subject to copyright protection. Thecopyright owner has no objection to the facsimile reproduction by anyoneof the patent document or the patent disclosure, as it appears in thePatent and Trademark Office patent file or records, but otherwisereserves all copyright rights whatsoever.37 CFR §1.71(d).

TECHNICAL FIELD

This disclosure pertains to powered vehicles, and more specifically tomotor vehicles, and concerns communications of data between a vehicleand a centralized server to enable various beneficial applications.

BACKGROUND OF THE INVENTION

The ubiquitous CAN bus (for controller area network) is a vehicle busstandard designed to allow microcontrollers and devices to communicatewith each other within a vehicle without a host computer. CAN bus is oneof five protocols used in the OBD-II vehicle diagnostics standard. TheOBD-II standard has been mandatory for all cars and light trucks sold inthe United States since 1996, and the EOBD standard has been mandatoryfor all petrol vehicles sold in the European Union since 2001 and alldiesel vehicles since 2004. CAN is a multi-master broadcast serial busstandard for connecting electronic control units (ECUs).

Each node is able to send and receive messages, but not simultaneously.A message consists primarily of an ID (identifier), which represents thepriority of the message, and up to eight data bytes. It is transmittedserially onto the bus. This signal pattern is encoded innon-return-to-zero (NRZ) and is sensed by all nodes. The devices thatare connected by a CAN network are typically sensors, actuators, andother control devices. In general, these devices are not connecteddirectly to the bus, but through a host processor and a CAN controller.In any event, the CAN networks are confined to the motor vehicle.

SUMMARY OF THE INVENTION

The following is a summary of the invention in order to provide a basicunderstanding of some aspects of the invention. This summary is notintended to identify key/critical elements of the invention or todelineate the scope of the invention. Its sole purpose is to presentsome concepts of the invention in a simplified form as a prelude to themore detailed description that is presented later.

In general, on-board electronic communications continue to evolve inmotor vehicles, but they remain confined in the vehicle. One feature ofthe present disclosure extends aspects of the on-board networks, sensorsand other nodes to a remote server location.

In another aspect of this disclosure, a remote server can acquire datafrom a motor vehicle, including on-board sensor data.

In still another aspect, sensor data can be used to remotely identify amotor vehicle at a remote server.

In still another aspect, sensor data can be used to remotely identify acurrent driver of a motor vehicle at a remote server.

Additional aspects and advantages of this invention will be apparentfrom the following detailed description of preferred embodiments, whichproceeds with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified block diagram illustrating selected components ofone example of a fleet management monitoring system consistent with thepresent disclosure.

FIG. 2 illustrates a server-based process to collect electronic sensordata from a remote vehicle.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

A problem arises in that the data communications ports on some vehiclesdo not provide a Vehicle Identification Number (VIN), which is a uniqueidentifier. Without the ability to uniquely identify a vehicle, a fleetmanagement system is severely constrained. For example, it cannotimplement an automated provision system to quickly provision the vehiclesystems with calibration parameters. In some case, such parameters maybe unique to the behavior of a vehicle. Downloaded parameters or otherdata may be used by on-board software. In some embodiments on-boardsoftware or systems may utilize driver behavior algorithms formonitoring driver behavior. Further, an automated system cannot collectdata from vehicles without having to manually correlate the data to thefleet vehicles, if possible, by some other means. Various advantageousfunctions can be implemented from a remote server given a way touniquely identify each vehicle.

In an embodiment, a computing device may be connected to a motorvehicle's diagnostic port or communication port to acquire vehiclesensor data, for example from various pressure, temperature, oxygen,fuel and other sensors typically installed on a motor vehicle for otherreasons. The computing device may be a mobile device such as a smartphone. The device may be connected to a port, for example an OBD port.The device may be connected by cable or short-range wireless connection(e.g., a Bluetooth® connection) to an on-board network.

Acquired sensor data may be wirelessly transmitted via the smart phoneto a remote server where the acquired sensor data can be stored and orcompared to a database of stored sensor data to identify the motorvehicle and for other functions. Acquired sensor data may also betransmitted via an on-board or embedded NAD (network access device).

Sensor data may be uploaded to the server in near-real time, and/orbuffered locally and uploaded by periodic or episodic, push or pullcommunication protocols. Acquired sensor data may be stored at a centralserver. Acquired data may be stored in a database coupled to a centralserver. It may be used to form stored baseline data. The determinedvehicle ID can be used by a backend server system to compare thehistorical operation of the vehicle to determine if there are anyanomalies associated with its behavior. In addition the vehicle ID canbe used to determine if any anomalies may be caused by the driveroperating the vehicle, as further explained below. Further, the vehicleID may be used for provisioning data or software from the server to thevehicle, especially to adapt it to current conditions.

In FIG. 1, a simplified block diagram illustrates the main components ofone example of a fleet management or driver behavior monitoring system.In this example, a motor vehicle's data communication port 100 or otherinterface is coupled, via a cable or wireless connection, to a computingand communications device, such as a user's “smart phone” 104. Forexample, a Bluetooth® connection may be used, or similar short-rangewireless connection, between the portable device and the vehicleport/adapter, but this connection can be made via any means available.

In an embodiment, the smart phone 104 communicates via the cellular datacommunication network 110 (aka “mobile network”), and IP gateway whereneeded, to a remote server (“back end system”) 120 which receives andstores and maintains data of several types. One type may be historicaldata 122. Historical data 122 may include, but is not limited to, thefollowing examples: (a) sensor data for vehicle identification; (b)historical driver and vehicle behavior data; (c) calibration parametersand other data for download to the vehicle and (d) geographic locationdata provided, for example, by an internal or external GPS sensor. Inaddition to historical data, the server system may include aprovisioning manager 130 for provisioning the computing device in thevehicle. The computing device in the vehicle may comprise a portabledevice, as illustrated, or in another embodiment one or more processors(not shown) that are embedded in the vehicle for various purposes.

In some embodiments, stored baseline sensor data includes sensor dataacquired from a corresponding motor vehicle during at least one knownsteady-state condition. To illustrate, a first steady state conditionmay be defined within a predetermined time window, for example 5seconds, after startup of the vehicle engine from a cold start. This maybe called a cold condition.

A second steady-state condition may be defined after expiration of atleast a predetermined minimum time period of continuous operation of thevehicle engine. For example, this period may be on the order of 5 or 10minutes. It may be called a “hot” or running condition. In someembodiments, the stored baseline sensor data includes sensor dataacquired from a corresponding motor vehicle during the cold condition.In some embodiments, the stored baseline sensor data includes dataacquired from a corresponding motor vehicle during the hot or runningcondition. An ensemble of multiple sensor readings, for example readingsfrom three or four different sensors, may be stored at the server andused to identify a remote vehicle. In some embodiments, the sensorreadings may be cold condition, hot condition, or a combination of thetwo types.

By way of illustration and not limitation, vehicle sensors used toprovide data may include the following:

-   -   engine coolant temperature    -   engine air temperature    -   fuel rail pressure    -   engine oil temperature    -   absolute throttle position limit    -   engine RPM at idle    -   Lambda exhaust oxygen sensor voltage

So, for example, engine RPM at idle may be acquired, at cold condition,as well as the same metric at a hot condition. The same data (hot andcold) may be acquired for fuel rail pressure and engine oil temperature,for a total of nine measurements. Data sets of this type may be used toidentify the vehicle. An elapsed time period may be used to delineatecold to hot. Or, a rate of change may be used to indicate a running(steady-state) condition. Other sensors may be used in addition, or inlieu of those mentioned. A greater number of sensors generally willbetter distinguish one vehicle from another. Comparison of acquired datato previously stored baseline data may be accomplished using knowndatabase query technologies. Fuzzy matching may be used.

In some implementations, said acquiring sensor data from the remotevehicle includes acquiring sensor data for at least three of theforegoing steady-state sensor output values; and wherein said comparingstep includes comparing the at least three steady-state sensor outputvalues to the corresponding stored baseline data.

Thus in one aspect of the present disclosure, a method of identifying avehicle may comprise a combination of characterizing the sensor datavalues that are read from the vehicle data communication port at knownsteady state vehicle conditions, and characterizing certain sensorvalues as the state of the vehicle is changing in a previouslycharacterized rate and direction of change. The accuracy of the vehiclesensor measurements preferably are on the order of <=+/−1 accuracy.

Other metrics may include dynamic measurement conditions. Examples ofdynamic measurements may include, without limitation, the following:

-   -   Engine idle at startup mapped to previously recorded engine cold        start temperatures.    -   Engine idle at specified hot engine temperatures    -   The duration of engine temperature change from cold start to hot        temp relative to a previously recorded average engine load over        the time it takes to change from cold temp to hot temp.    -   GPS location to differentiate between two vehicles with similar        sensor data values.

In an embodiment, we propose to characterize a vehicle based in part onsteady state sensor output values. This would involve the measurement ofvehicle sensor data provided by the data communication port under steadystate vehicle connections such as but not limited to the following:

Engine coolant temperature, typically measured in a range of −40° F. to419° F. (−40° C. to 215° C.). This sensor typically has an accuracy of+/−5% which equates to a result in deviation from one sensor output toanother of +22.95° F. (+5° C.) to −22.95° F. (−5° C.) relative to theactual temperature of the coolant. With this output deviation fromsensor to sensor the output can be used along with other types sensoroutputs to develop a “finger print” for the vehicle.

Engine air temperature is typically measured in a range of −40° F. to419° F. (−40° C. to 215° C.). This sensor typically has a accuracy of+/−5% which equates to can result in a deviation from one sensor toanother of +22.95° F. (+5° C.) to −22.95° F. (−5° C.) relative to theactual temperature of the engine intake air. With this output deviationfrom sensor to sensor the output can be used along with other typessensor outputs to develop a “finger print” for the vehicle.

Fuel Rail Pressure will vary greatly from one make and model vehicle toanother. For same make and model vehicles there will be a deviation fromone vehicle to another that is a function of the accuracy of the fuelpressure regulator and the fuel pressure sensor. Even if these twodevices are 1% accurate the total accuracy will be +/−2%. This is ameasurable sensor output that is unique to a specific vehicle.

Engine oil temperature will vary greatly from one make and model vehicleto another. For same make and model vehicles there will be a deviationfrom one vehicle to another that is a function oil viscosity, engineblock mass and thermal dissipation, and oil temperature accuracy whichtypically is +/−5%. This is a measurable sensor output that is unique toa specific vehicle.

Absolute throttle position is measured in 0 to 100% maximum throttleopening. From same vehicle make and model or for different vehicle makeand model the minimum value could be unique. This is due to themechanical closed throttle limit which is often governed by an air idleset screw or throttle casting closed position stop.

Engine RPM: This value is usually within 1% of the actual the engineRPM, however the engine RPM is a factor of many vehicle specificvariables which affect the engine RPM at any steady state condition.These vehicle specific variables include the temperature of the engineand air at steady state condition, upstream of the throttle air pressuredrop due to air filter cleanliness. How well each engine cylinder isgenerating cylinder pressure during the fuel and air combustion process,and the closed loop engine idle RPM where a desired measured air fuelratio has been obtained by the engine management system that is relativeto stoichiometric air fuel ratio at the desired engine RPM for the fueltyped used. This desired engine RPM can be the product of the enginemanagement system learned output that results in the best emissionoutput of the engine at that steady state condition and it will varyfrom one vehicle to another.

Lambda sensor. For the specific fuel used in the vehicle the Lambdasensor voltage output range can vary from one sensor to another due toage of the sensor, sensor accuracy, sensor manufacturing techniques foroxygen reference cell. The number of active lambda sensors that can bemeasured can be used to determine difference for vehicle make and modelsthat have engines with different number of cylinders or differencesophistication of the engine management system which is responsible forcontrolling engine output relative to engine emissions. In anembodiment, several of the foregoing metrics are used in combination todetermine a unique identification or profile of a vehicle.

In another aspect, we characterize the vehicle's dynamic state change todetermine a rate of change profile for sensor output values. Forexample:

-   -   1. Engine idle RPM as the vehicle changes temp from cold start        to a predefined hot operating temperature.    -   2. Engine oil temperature change relative to engine coolant        temperature change from a cold start engine temperature to a        predefined hot engine temperature.

Some embodiments thus may be summarized as follows: Acomputer-implemented method of identifying a motor vehicle comprising:acquiring first sensor data from the vehicle during a first steady stateoperating condition of the vehicle; acquiring second sensor data fromthe vehicle during a second steady state operating condition of the samevehicle; wherein the first and second sensor data each include dataacquired from no less than three sensors installed on board the vehicle,the first and second data being acquired from the same sensors atdifferent times; and storing the acquired first and second sensor dataso as to form baseline sensor data for use in subsequent identificationof the vehicle.

A method consistent with the present disclosure may further includecomparing the first and second sensor data to stored baseline sensordata; and forming an identifier of the vehicle based on the saidcomparing step.

FIG. 2 is a simplified flow diagram illustrating a server-based process200 to collect electronic sensor data from a remote vehicle. In thefigure, a wireless communication link 202 is formed between a centralserver, for example, a fleet management system, and a remote vehicle.The link may be over the wireless telecom network. The link may utilizein-band signaling to transmit data over a voice channel. The link mayutilize a data service.

If sensor data is buffered at the vehicle and is ready, decision 204, itis uploaded, block 206. If it is not ready, the process may loop at 208.Uploaded data may undergo error correction in the process, andoptionally it may be scrubbed to help ensure valid data, block 210.

After data is ready, a database coupled to the server, for example, abaseline database, may be queried to look for matching data, block 220.Matching baseline sensor data may be used to identify the vehicle. If aunique match is found, decision 222, the data may be added to adatabase, block 230. The process may loop via 240 in some cases toacquire additional data. If a unique match was not found initially at222, an effort may be undertaken to disambiguate among plural vehiclesreporting similar sensor values, for example, based on acquiringcorresponding location data of each of the vehicles. Location data maybe acquired from GPS receiver in the vehicle. A GPS receive may becoupled to an on-board network so that the location data is accessible.In the case of using a mobile device such as a smart phone forcommunication with the server, the smart phone embedded GPS receiver maybe used to acquire location of a vehicle. If disambiguation does notsucceed, decision block 232, additional sensor data may be requested,block 250, and the matching process repeated via loop 252.

Driver Behavior

Another feature of the present disclosure involves acquiring sensordata, which may be buffered, stored, or transmitted in near-real time,and analyzing that sensor data to infer characteristics of driverbehavior. Data may be accumulated over time for a given driver to form aprofile. Deviation from the profile may indicate driver impairment, dueto medical or other factors. Profiles based on sensor data also may beused to infer the identity of a current driver of a vehicle.

Fuel Efficiency

Another feature of the present disclosure involves acquiring sensordata, and based on the stored data, calculating a mileage rate or fuelefficiency of the motor vehicle. The mileage rate refers to milestraveled per gallon of liquid fuel, or per kilowatt-hour of electricalenergy for an electric vehicle. Using the techniques above, fuelefficiency may be determined for each vehicle, under various conditions.Deviation from the normal fuel efficiencies may indicate a maintenanceissue that requires attention. If no maintenance issue exists then thedifference in calculated average fuel efficiency can also be used touniquely identify the vehicle if driver behavior can be ruled out as areason for fuel efficiency variability.

In some cases, changes in vehicle performance as reflected in sensordata may be due to driver behavior rather than maintenance issues.Distinguishing between these two causes may be achieved by analysis ofdata acquired over time. Other case —very different vehicle causes verydifferent readings, not the driver.

It will be obvious to those having skill in the art that many changesmay be made to the details of the above-described embodiments withoutdeparting from the underlying principles of the invention. The scope ofthe present invention should, therefore, be determined only by thefollowing claims.

1. A method for remotely identifying a motor vehicle, comprising: (a)electronically acquiring sensor data from a plurality of electronicsensors installed in the vehicle; (b) transmitting the acquired sensordata via a wireless link, from the vehicle to a remote server; (c) atthe remote server, receiving the acquired sensor data and comparing theacquired sensor date to stored baseline data; and (d) identifying themotor vehicle based on the said comparison.
 2. The method according toclaim 1 wherein the stored baseline data includes sensor data previouslyacquired from a plurality of sensors on board each one of a plurality ofmotor vehicles.
 3. The method according to claim 2 wherein the storedbaseline data includes, for a selected vehicle, data acquired from atleast three sensors selected from the group consisting of the followingsensors— engine coolant temperature engine air temperature fuel railpressure engine oil temperature absolute throttle position limit engineRPM at idle Lambda exhaust oxygen sensor voltage.
 4. The methodaccording to claim 3 wherein the stored baseline data corresponding toat least one of the selected sensors includes first data acquired undera first operating condition of the corresponding motor vehicle, andsecond data acquired under a second operating condition of thecorresponding motor vehicle.
 5. The method according to claim 4 whereinthe first operating condition of the corresponding motor vehicle is acold condition and the second operating condition of the correspondingmotor vehicle is a steady-state operating condition.
 6. The methodaccording to claim 5 wherein the steady-state operating condition isdefined as a predetermined period of time after startup of the vehicle.7. The method according to claim 3 including characterizing a vehicle'sdynamic state change to determine a rate of change profile for at leastone of the selected sensors for a given vehicle, and adding the dynamicstate change profile to the stored baseline data for identifying thecorresponding vehicle.
 8. The method according to claim 7 wherein thedynamic state change is determined from a cold start condition to apredefined hot operating temperature.
 9. The method according to claim 3wherein said identifying the motor vehicle includes disambiguating amongplural vehicles reporting similar sensor values, based on acquiringcorresponding location data of each of the vehicles.
 10. The methodaccording to claim 9 wherein said acquiring corresponding location dataof each of the vehicles from a GPS receiver located in the respectivevehicle.
 11. A computer-implemented method comprising: acquiringelectronic sensor data from a remote motor vehicle; repeating theacquiring step so as to accumulate the electronic sensor data over aselected period of time; correlating the accumulated electronic sensordata to a database of baseline sensor data so as to identify acorresponding motor vehicle; analyzing the accumulated electronic sensordata for a corresponding vehicle driver so as to form a driver profileassociated with the identified motor vehicle and the correspondingvehicle driver; and storing the driver profile in a central serverdatabase of plural driver profiles.
 12. The method of claim 11 whereinthe electronic sensor data is transmitted wirelessly from the motorvehicle to a central server.
 13. The method of claim 12 wherein theelectronic sensor data is acquired over an on-board network of the motorvehicle for transmission to a central server.
 14. The method of claim 12wherein the electronic sensor data is acquired through a connection toan OBD port of the motor vehicle for transmission over a wirelesstelecommunication link to a central server.
 15. The method of claim 14including acquiring the data in a mobile device coupled to the OBD portof the motor vehicle and substantially immediately transmitting theacquired data from the mobile device to a central server in the wirelesstelecommunication link.
 16. The method of claim 14 includingtransmitting the electronic sensor data to a central server insubstantially real time.
 17. The method of claim 11 and furthercomprising: acquiring current electronic sensor data from a remote motorvehicle; and comparing the new electronic sensor data to the centralserver database of plural driver profiles to identify a current driverof a vehicle.
 18. The method of claim 11 and further comprisingcomparing the new electronic sensor data to previously stored sensordata in the database to detect a change in behavior of the driver. 19.The method of claim 11 and further wherein the driver profile includes,for a selected vehicle, data acquired from at least three sensorsselected from the group consisting of the following sensors— enginecoolant temperature engine air temperature fuel rail pressure engine oiltemperature absolute throttle position limit engine RPM at idle Lambdaexhaust oxygen sensor voltage.
 20. The method of claim 11 and furthercomprising comparing the new electronic sensor data to previously storedsensor data in the database to detect a maintenance issue of thecorresponding vehicle.